Book Image

Functional Python Programming - Second Edition

By : Steven F. Lott
Book Image

Functional Python Programming - Second Edition

By: Steven F. Lott

Overview of this book

If you’re a Python developer who wants to discover how to take the power of functional programming (FP) and bring it into your own programs, then this book is essential for you, even if you know next to nothing about the paradigm. Starting with a general overview of functional concepts, you’ll explore common functional features such as first-class and higher-order functions, pure functions, and more. You’ll see how these are accomplished in Python 3.6 to give you the core foundations you’ll build upon. After that, you’ll discover common functional optimizations for Python to help your apps reach even higher speeds. You’ll learn FP concepts such as lazy evaluation using Python’s generator functions and expressions. Moving forward, you’ll learn to design and implement decorators to create composite functions. You'll also explore data preparation techniques and data exploration in depth, and see how the Python standard library fits the functional programming model. Finally, to top off your journey into the world of functional Python, you’ll at look at the PyMonad project and some larger examples to put everything into perspective.
Table of Contents (22 chapters)
Title Page
Packt Upsell

Chapter 9. More Itertools Techniques

Functional programming emphasizes stateless programming. In Python, this leads us to work with generator expressions, generator functions, and iterables. In this chapter, we'll continue our study of the itertools library, with numerous functions to help us work with iterable collections.

In the previous chapter, we looked at three broad groupings of iterator functions. They are as follows:

  • Functions that work with infinite iterators, which can be applied to any iterable or an iterator over any collection; they will consume the entire source
  • Functions that work with finite iterators, which can either accumulate a source multiple times, or produce a reduction of the source
  • The tee() iterator function, which clones an iterator into several copies that can each be used independently

In this chapter, we'll look at the itertools functions that work with permutations and combinations. These include several functions and a few recipes built on these functions. The...